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| 1 | Metabolic investigations in patients with hepatitis B and C显示文摘AIM:To investigate the similarities and dissimilarities in patients with hepatitis B and hepatitis C,clinically and metabolically. METHODS:Fifty patients with hepatitis B virus and hepatitis C virus infection were included in this study, along with fifty healthy controls for comparison purposes.Intravenous blood(10 mL)samples from patients and healthy subjects were collected and made to clot before serum was separated and immediately levels of the enzymes,alkaline phosphatase(ALK),creatinine phosphokinase(CPK),lactate dehydrogenase (LDH),serum glutamate oxaloacetate transaminase(sGOT)and serum glutamate pyruvate transaminase(sGPT)were determined by a kit method.For total con-tent of each metal the serum samples were analyzed using atomic absorption spectrophotometry.Levels of cholesterol,triglycerides,urea,creatinine and uric acid were determined using a kit method on Microlab 300. RESULTS:Serum magnesium and copper levels remained unchanged,whereas the concentration of zinc decreased and iron increased significantly in both groups of patients.Total antioxidant activity was significantly decreased in both hepatitis B and C.Among the enzymes analyzed,ALK,s-GPT,LDH and s-GOT were all significantly increased in both patients with hepatitis B and C whereas CPK was significantly decreased in patients with hepatitis B and remained unchanged in patients with hepatitis C. CONCLUSION:The information accumulated by this study will help provide a better understanding of involved metabolic processes in order to design appropriate therapeutic approaches for treating these patients,so they can recover and lead normal lives. | Abdul Aziz Mastoi Bikha Ram Devrajani Syed Zulfiquar Ali Shah Qasim Rohopoto Sikander Ali Memon Marya Baloch Ghulam Ali Qureshi Waqas Sami | 2010 | World Journal of Gastroenterology2010，16，5： | 2 |
| 2 | A Novel Parallel Computing Confidentiality Scheme Based on Hindmarsh-Rose Model显示文摘Due to the inherent insecure nature of the Internet,it is crucial to ensure the secure transmission of image data over this network.Additionally,given the limitations of computers,it becomes evenmore important to employ efficient and fast image encryption techniques.While 1D chaotic maps offer a practical approach to real-time image encryption,their limited flexibility and increased vulnerability restrict their practical application.In this research,we have utilized a 3DHindmarsh-Rosemodel to construct a secure cryptosystem.The randomness of the chaotic map is assessed through standard analysis.The proposed system enhances security by incorporating an increased number of system parameters and a wide range of chaotic parameters,as well as ensuring a uniformdistribution of chaotic signals across the entire value space.Additionally,a fast image encryption technique utilizing the new chaotic system is proposed.The novelty of the approach is confirmed through time complexity analysis.To further strengthen the resistance against cryptanalysis attacks and differential attacks,the SHA-256 algorithm is employed for secure key generation.Experimental results through a number of parameters demonstrate the strong cryptographic performance of the proposed image encryption approach,highlighting its exceptional suitability for secure communication.Moreover,the security of the proposed scheme has been compared with stateof-the-art image encryption schemes,and all comparison metrics indicate the superior performance of the proposed scheme. | Jawad Ahmad Mimonah Al Qathrady Mohammed SAlshehri Yazeed Yasin Ghadi Mujeeb Ur Rehman Syed Aziz Shah | 2023 | Computers, Materials & Continua2023，76，8： | 0 |
| 3 | Machine learning empowered COVID-19 patient monitoring using non-contact sensing:An extensive review显示文摘The severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),which caused the coronavirus disease 2019(COVID-19)pandemic,has affected more than 400 million people worldwide.With the recent rise of new Delta and Omicron variants,the efficacy of the vaccines has become an important question.The goal of various studies has been to limit the spread of the virus by utilizing wireless sensing technologies to prevent human-to-human interactions,particularly for healthcare workers.In this paper,we discuss the current literature on invasive/contact and non-invasive/noncontact technologies(including Wi-Fi,radar,and software-defined radio)that have been effectively used to detect,diagnose,and monitor human activities and COVID-19 related symptoms,such as irregular respiration.In addition,we focused on cutting-edge machine learning algorithms(such as generative adversarial networks,random forest,multilayer perceptron,support vector machine,extremely randomized trees,and k-nearest neighbors)and their essential role in intelligent healthcare systems.Furthermore,this study highlights the limitations related to non-invasive techniques and prospective research directions. | Umer Saeed Syed Yaseen Shah Jawad Ahmad Muhammad Ali Imran Qammer H.Abbasi Syed Aziz Shah | 2022 | Journal of Pharmaceutical Analysis2022，12，2： | 0 |
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